# Principal Engineer – Scale-Up GPU Networking (HPC / AI)

**Company**: Hewlett Packard Enterprise
**Location**: Bengaluru, Karnātaka
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://hpe.wd5.myworkdayjobs.com/en-US/Jobsathpe/job/Bengaluru-Karntaka-India/Principal-Engineer---Scale-Up-GPU-Networking--HPC---AI-_1213784-3?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_2308d466-de1

## Description

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world.

**Job Description:**

You will be a Principal Engineer in the High Performance Computing, AI and Labs team, focusing on delivering innovative solutions that accelerate our customers’ digital transformation, enabling them to tackle their complex, and data-intensive workloads.

**Key Responsibilities:**

- Architect & Deliver Scale-Up Networking: Design and implement GPU-aware networking paths for high-bandwidth, low-latency intra-node communication. Develop and optimize GPU → NIC → GPU data movement, shared memory models, and DMA pathways.

- GPU Ecosystem Integration: Work with NVIDIA CUDA, NVLink, NCCL, and AMD ROCm, InfinityFabric, RCCL teams to integrate and optimize scale-up communication semantics. Drive improvements to DMA engines, BAR mappings, ATS/IOMMU, and GPU memory registration workflows.

- Runtime & Communication Stack Development: Enhance and extend Libfabric, UCX, CXI, SHMEMX, OpenMPI for GPU-accelerated scale-up workflows. Optimize communication collectives, transport layers, and GPU-direct capabilities.

- Multi-NIC / NUMA Performance Optimization: Characterize and tune multi-NIC per socket, NUMA-zone mapping, GPU locality, CQ/queue design, and CPU/GPU topology optimization.

- Upstreaming & Architecture Influence: Lead upstream contributions to open-source projects (OFI, UCX, OpenMPI, RCCL/NCCL enablement). Partner with HPC/AI ecosystem teams to shape future architectures.

- Debugging, Performance, and Quality: Own complex debugging across driver, runtime, GPU, kernel, and user-space boundaries. Develop profiling workflows using Nsight, ROCm tools, eBPF, perf, etc.

**What you need to bring:**

- 10–15+ years building high-performance networking, GPU, or kernel-level software.

- Deep expertise in C/C++, Linux internals, memory management, RDMA, PCIe, IOMMU, ATS, DMA engines.

- Strong understanding of CUDA, ROCm, GPU memory models, P2P, GDS (GPUDirect Storage), GDR (GPUDirect RDMA).

- Hands-on experience with MPI, SHMEM, Libfabric, UCX, or similar communication stacks.

- Proven experience driving architecture, cross-org technical decisions, and upstream contributions.

- Ability to mentor senior engineers, influence multi-team designs, and own end-to-end delivery.

**Preferred Qualifications:**

- Experience with NIC architecture (CXI, RoCE, Infiniband, Slingshot, NVLink Switch).

- Experience optimizing collectives (AllReduce/AllGather) on GPUs.

- Background contributing to open-source HPC/AI libraries.

- Familiarity with HPC system architecture, NUMA tuning, and multi-accelerator systems.

**What We Can Offer You:**

- Health & Wellbeing: Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.

- Personal & Professional Development: Specific programs catered to helping you reach any career goals you have.

- Unconditional Inclusion: We are unconditionally inclusive in the way we work and celebrate individual uniqueness.

## Skills

### Required
- C/C++
- Linux
- GPU
- Networking
- RDMA
- PCIe
- IOMMU
- ATS
- DMA engines
- CUDA
- ROCm
- MPI
- SHMEM
- Libfabric
- UCX

### Nice to have
- NIC architecture
- Collectives optimization
- Open-source HPC/AI libraries
- HPC system architecture
- NUMA tuning
- Multi-accelerator systems

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Source: [Apply at hpe.wd5.myworkdayjobs.com](https://hpe.wd5.myworkdayjobs.com/en-US/Jobsathpe/job/Bengaluru-Karntaka-India/Principal-Engineer---Scale-Up-GPU-Networking--HPC---AI-_1213784-3?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)